Blog | Safience - Identity Service for Threats and Victims

Known-offender identification at the bank branch: what it is and what it is not

Posted on October 12, 2026October 12, 2026 by Safience

A bank will spend weeks learning who a loan applicant is. It will check identity, credit, sanctions lists and account history before it lends a dollar. Then it opens the branch doors at nine and knows almost nothing about the people who walk up to the teller line.

That gap is not theoretical. The FBI’s most recent Bank Crime Statistics report counts 1,263 robberies of financial institutions in 2023. Firearms were used in 230 of them and weapons were threatened in another 539. Twenty-one people were taken hostage. And robbery is only the loudest branch crime. Federal regulators report that suspicious activity reports for check fraud nearly doubled between 2021 and 2023, and much of that paper still crosses a counter in person.

Fraud teams watch the transaction. Almost nobody watches for the known offender before the transaction starts.

What known-offender identification means

Known-offender identification answers one narrow question: is someone who matches a verified law-enforcement record, relevant to this branch, on the premises right now?

It is not a background check on every customer. It is not a watchlist the bank builds from its own suspicions. And it is not surveillance of the public. The comparison set is a defined list of records that a court or agency has already created: active felony warrants, fugitives, registered sex offenders where relevant, and missing persons a branch employee might help find.

How it works at a branch

With RTIS, the Real-Time Threat Identification System, a branch uses the cameras it already has at the entrance.

Capture. A single small still image is taken at the door. There is no video stream to Safience and nothing is recorded.
Compare. The image is checked against relevant records in UMbRA, the law-enforcement-sourced identity database, which holds 58.5M+ records from law-enforcement sources only.
Discard. If there is no match, the image is deleted at once. The bank never learns who walked in, and no biometric template is stored.
Review. A potential match goes to a trained analyst, who checks the record, its currency and the context before anything is sent.
Alert. Only a verified, relevant match becomes an alert to the branch’s designated contact, typically in under a minute, with guidance on what to do next.

Most customers are never part of the process at all beyond step three. That is the design.

What it is not

It is not a way to refuse service to people with old convictions. Relevance rules decide which records matter at a bank, and a decade-old misdemeanor is not one of them.

It is not automated. No alert reaches the branch without a human decision, and the branch decides what to do with it under its own policy.

It is not a credit tool or a KYC substitute. Account onboarding has its own legal framework. Branch identification is about physical safety on the premises.

Where it helps most

The teller line. A person with an active warrant for armed robbery walking into a branch is precisely the alert a branch manager wants before that person reaches the counter, not after.

Repeat check presenters. A fraud offender with an active warrant may try more than one branch in a day. A verified alert at the second branch can stop the third.

Employees at risk. Bank staff are sometimes followed to work by someone with a history of violence toward them. A person with an active warrant tied to a domestic-violence case is a legitimate, specific alert.

Insider risk. Customers are only half the picture. eMotive continuous, consent-based employee monitoring tells a bank, with the employee’s written consent, when a team member is newly arrested, rather than waiting for the next periodic background check.

Questions to ask any provider

Is every record in the comparison set sourced from law enforcement, and can you name the sources?
What happens to an image that does not match, and how quickly?
Do you keep video or biometric templates? (The right answer is no.)
Who reviews a match before the branch is alerted?
How do your relevance rules work, and can we see them?
How do you handle biometric privacy law in each state where we have branches?

That last question matters. Illinois, Texas, Washington and a growing number of cities set their own rules on biometric information. Our state privacy policy pages explain how Safience operates in each.

The short version

Banks already accept that knowing who they are dealing with is part of managing risk. Known-offender identification extends that idea from the loan file to the lobby, using records that already exist, a human in the loop, and nothing kept on anyone who is not a match.

See how it fits your branches on our Safience for banks page, or request a Threat Mapping Assessment.

Frequently asked questions

Does Safience record video in bank branches?

No. Safience works from a single small still image and never receives, records or stores video.

What happens to images of customers who are not a match?

They are deleted immediately. No biometric template is created or kept.

Who decides whether a match is real?

A trained Safience analyst reviews every potential match before any alert reaches the branch. The branch then acts under its own policy.

Which records are used?

Only verified law-enforcement records relevant to a bank setting, such as active felony warrants and fugitives, drawn from UMbRA, the law-enforcement-sourced identity database.

Sources

FBI, Bank Crime Statistics 2023. https://www.fbi.gov/file-repository/reports-and-publications/bank-crime-statistics-2023-091724.pdf/view
Consumer Compliance Outlook (Federal Reserve), “Responding to Counterfeit Instrument Scams and Mail-Related Check Fraud,” 2025, citing FinCEN. https://www.consumercomplianceoutlook.org/articles/2025/second-issue-2025/responding-to-counterfeit-instrument-scams-and-mail-related-check-fraud

Featured photo by Anton Acosta on Unsplash.

Identity intelligence starts with a record, not a face

Posted on October 12, 2026October 12, 2026 by Safience

A face search can do its job perfectly and still put the wrong person in a cell.

That is the uncomfortable lesson in two cases out of Jacksonville, Florida, collected by Biometric Update on 1 October. In the first, a convicted offender lifted photos from another man’s Facebook account and used them on a dating app to contact a minor. Investigators ran those photos through a face search. The search returned the man in the photos, which was correct. He was arrested, jailed and separated from his children. He had done nothing. The photos were his. The crime was not.

In the second, a Charlotte man named Jalil Richardson was matched from surveillance footage against a fake Georgia ID that someone else had used to sell a stolen vehicle. A warrant followed. Nobody first checked whether he had been in Florida at all.

Neither case is really about algorithm accuracy. In both, the software found a face that resembled the input. The failure came one step later, when a resemblance was treated as an identity.

The face is not the selector

There is a model of this technology spreading through the industry that starts with a face and works outward. Run the face, pull every image that looks similar, crawl the open web for names, addresses, employers and associates, and assemble a profile. The face becomes the selector, and everything attached to it is presumed to belong to the person in front of the camera.

That model has a name problem as well as a privacy problem. It is increasingly sold as “identity intelligence.” We use that phrase too, and we mean almost the opposite.

For us, identity intelligence starts with a record that already exists, created by a law-enforcement agency through due process: a booking, a felony warrant, a conviction, a sex-offender registration, a missing-person report. The question is never “who could this face be?” The question is narrower and easier to defend. Does this person match a specific, verified record that is relevant to this facility, today?

Three rules that follow from that

Start from verified records only. UMbRA, the law-enforcement-sourced identity database, holds 58.5M+ records and draws on nothing else. No social media. No news. No credit files. No scraped photos. If a record did not come from a law-enforcement source, it is not in the comparison set. A stolen Facebook photo cannot become a suspect because Facebook was never searched.

Compare to a record, not to the world. When a comparison is needed, it is one-to-one against the record in question, the way QAPLA one-to-one face comparison works, rather than one-to-many against everything on the internet. A non-match is discarded immediately. No biometric template is kept.

Treat every result as a lead. Nothing we produce is an identification on its own. There is no predictive score and no automated decision about anyone’s liberty.

What a human reviewer is for

Photo by MJ Duford on Unsplash

Between the comparison and any alert, a trained analyst looks at the record and the capture side by side and asks the questions the Jacksonville investigators skipped. Is the record current? Is the warrant still active? Does the context make sense? Is there a reason to doubt this is the same person? If the answer is unclear, the alert does not go out.

That review is not a formality. It is the part of the system that knows a resemblance is not a fact.

Detroit learned this the expensive way. After Robert Williams was wrongly arrested on a face match, the city settled in June 2024 and agreed that police would no longer make arrests based solely on facial recognition results, or on photo lineups that follow straight from a face search. Civil-rights groups called it the strongest such policy in the country. It is also simply good practice, and it matches the facial recognition use policy we recommend to our own law-enforcement partners.

The test for any vendor

If you are evaluating identity technology for a police department, a casino floor, a hospital or a bank branch, three questions sort the field quickly.

Where does the comparison set come from, and can the vendor name every source?
What happens to a non-match, and how long does it exist?
Who is the human between the result and the action, and what are they trained to check?

A vendor that cannot answer all three in plain language is selling a face search with a profile attached. The Jacksonville cases show where that leads.

For more on why the record matters more than the comparison, see A match is only as good as the record behind it. For how consent and biometric rules differ by jurisdiction, see our state privacy policy pages.

Sources

Biometric Update, “With wrongful arrests, Jacksonville police show how not to use facial recognition,” 1 Oct 2026. https://www.biometricupdate.com/202610/with-wrongful-arrests-jacksonville-police-show-how-not-to-use-facial-recognition
ACLU of Michigan, “Civil Rights Advocates Achieve the Nation’s Strongest Police Department Policy on Facial Recognition Technology,” June 2024. https://www.aclumich.org/press-releases/civil-rights-advocates-achieve-nations-strongest-police-department-policy-facial/
Scripps News, “Detroit police can no longer make arrests based only on facial recognition results after lawsuit,” 2024. https://www.scrippsnews.com/us-news/detroit-police-can-no-longer-make-arrests-based-only-on-facial-recognition-results-after-lawsuit

Featured photo by Ilya Semenov on Unsplash. Inline photo by MJ Duford on Unsplash.

Biometrica Systems now operates as Safience

Posted on October 12, 2026October 12, 2026 by Safience

Las Vegas, NV, October 1, 2026 Biometrica Systems, Inc. now does business as Safience. The change is one of name only. The legal entity, its Nevada private investigator license (PILB #1295), its contracts and its agency agreements are unchanged, and every product continues without interruption.

Safience is an identity service for threats and victims. It helps law enforcement and regulated facilities such as casinos, hospitals, schools, banks and venues learn, within about a minute, when a person who matches a verified law-enforcement record relevant to that site is present, and helps locate missing and trafficked people. A trained analyst reviews every potential match before anyone is alerted.

“For ten years the work has been the same: help people find the threats and the victims hiding in plain sight, without watching everyone else,” said Wyly Wade, CEO and Chairman. “Safience is the name that finally says what we do. Nothing about how we protect privacy changes with it.” [DECISION: QUOTE APPROVAL]

The Safience platform includes:

UMbRA, the law-enforcement-sourced identity database, with 58.5M+ records and no social, credit or commercial data.
RTIS, the Real-Time Threat Identification System, which alerts a facility to known, verified threats such as active felony warrants.
RVIS, the Real-Time Victim Identification System, which helps identify and locate missing and trafficked persons.
QAPLA one-to-one face comparison, for investigators confirming whether two images show the same person.
eMotive continuous, consent-based employee monitoring, protected by US Patents 11,928,749 B2 and 12,536,604 B2.

Customers and partners do not need to take any action. Existing links to biometrica.com redirect to the matching Safience pages, and mail sent to existing biometrica.com addresses continues to be delivered. [DECISION: add “Staff email moves to @safience.io by 30 November 2026.” only if approved; otherwise delete this marker]

More on the legal entity and the change is at safience.io/formerly-biometrica.

About Safience

Safience is the identity service for threats and victims, operated by Biometrica Systems, Inc. Its platform works from verified law-enforcement records, never mass surveillance. It stores no biometric identifiers, discards non-matches immediately, keeps no video, and puts a trained human analyst between every result and every alert. Safience serves law enforcement, gaming, healthcare, education, financial institutions and public venues. Learn more at https://safience.io.

Media contact: [DECISION: NAME, EMAIL @safience.io, PHONE]

Clearview AI alternatives: what to ask before you buy face search

Posted on October 12, 2026October 12, 2026 by Safience

People look for an alternative to Clearview AI for different reasons. An agency’s counsel may not want to defend a web-scraped database in court. A city may have a policy that rules it out. A private business may have learned it cannot buy it at all: under a 2022 settlement with the ACLU, Clearview is permanently barred, nationwide, from making its faceprint database available to most private companies.

Whatever brings you here, most comparison lists rank tools on match accuracy and price. Both matter. But the question that decides whether a tool is defensible comes first. What is in the database you are searching against?

Two different kinds of face technology

Open-web face search compares a face against images gathered from the public internet. What comes back is a set of similar-looking faces and the pages they were found on. Any one of those images could be someone else’s photo, reposted by someone else, attached to someone else’s name. In September, reporting first published by Wired described a Clearview prototype called InquiryIQ that uses xAI’s Grok model to connect a face match to associates, social accounts and other personal details. That is a step further from “is this the same person?” and closer to building a profile.

Record-bound identification compares only against records that law enforcement has already created through due process: bookings, warrants, convictions, registrations, missing-person reports. The question is narrow. Does this person match a specific, verified record?

These are different products for different jobs. The mistake is buying one while believing you have the other.

Six questions to ask any vendor

Can you name every source in the comparison set? If the answer includes “publicly available images,” ask which sites, and whether those people consented.
Does the set include social media, news photos or scraped images? A yes is not automatically disqualifying for every use. It is a fact your counsel will need.
Is the comparison one-to-one or one-to-many, and when? Confirming that two images show the same person is a different act from searching a face against millions.
What happens to the probe image and to non-matches? Ask how long they exist and whether any template is stored.
Who reviews a result before anyone acts on it? Look for a trained human, a documented checklist and a rule that a match alone is never grounds for an arrest.
How do you handle state biometric law where we operate? Illinois, Texas and Washington have their own statutes, and a growing number of cities set rules of their own.

Where Safience fits

Safience is a record-bound identity service. It is not an open-web search engine, and it does not try to be.

UMbRA, the law-enforcement-sourced identity database, holds 58.5M+ records and draws on nothing else. No social media, no news, no commercial data.
QAPLA one-to-one face comparison lets an investigator confirm whether two images show the same person.
RTIS, the Real-Time Threat Identification System, tells a facility when someone matching a relevant, verified record is on site, after a trained analyst has reviewed the match.
RVIS, the Real-Time Victim Identification System, helps identify and locate missing and trafficked people.

Non-matches are deleted immediately and no biometric template is kept. Safience never receives, records or stores video.

If your investigation depends on finding a face anywhere on the internet, Safience is not that tool. If it depends on knowing whether a person matches a verified law-enforcement record, and being able to explain exactly how you found out, it is.

For a plain-language account of what goes into the database and what never does, read What goes into UMbRA. For the full product set, see Safience solutions.

Frequently asked questions

Is Safience a direct replacement for Clearview AI?

No. Clearview searches images collected from the open web. Safience compares only against verified law-enforcement records, so it answers a narrower question with a documented source behind every result.

Can private businesses use Safience?

Yes. Casinos, hospitals, banks and other facilities receive a reviewed alert when someone on site matches a record relevant to that setting. They never browse or search the database themselves.

Does Safience use social media or scraped photos?

No. Every record comes from a law-enforcement or criminal-justice source.

Does Safience store faces of people who are not a match?

No. A non-matching image is deleted immediately and no biometric template is created or kept.

Sources

ACLU, “In Big Win, Settlement Ensures Clearview AI Complies With Groundbreaking Illinois Biometric Privacy Law,” 9 May 2022. https://www.aclu.org/press-releases/big-win-settlement-ensures-clearview-ai-complies-with-groundbreaking-illinois
Crypto Briefing, “Clearview AI quietly tests InquiryIQ tool powered by xAI’s Grok model,” 10 Sep 2026, citing Wired. https://cryptobriefing.com/clearview-ai-inquiryiq-grok-xai/

Featured photo by Elena Mozhvilo on Unsplash.

What goes into UMbRA, the law-enforcement-sourced identity database, and what never does

Posted on October 12, 2026October 12, 2026 by Safience

The question we hear most from police chiefs, casino compliance officers and hospital security directors is a simple one. What is actually in the database?

UMbRA, the law-enforcement-sourced identity database, is the record set behind every Safience alert. It holds 58.5M+ records and adds tens of thousands of new arrest and booking records every day. The live count is on the UMbRA identity database page.

What goes in

Every record comes from a law-enforcement or criminal-justice source. The categories are:

Booking and arrest records
Convictions
Felony warrants
Sex-offender registrations
Probation and parole records
Missing-persons reports

That is the whole list.

What never goes in

No social media. No news photos. No credit files. No consumer, marketing or commercial data. No images scraped from the open web. No video from any facility we serve.

This is a deliberate limit, not a gap we plan to fill. A record that came from a law-enforcement process has a known origin, a date and an agency behind it. A photo pulled from a public profile has none of that, and treating it as evidence is how innocent people end up arrested. We wrote about two recent cases in Identity intelligence starts with a record, not a face.

Who can search it

Not the public, and not our commercial customers. Direct search is limited to credentialed law-enforcement users, with role-based access and an audit trail on every query.

A casino, hospital or bank never browses the database. It receives an alert only when a person on its premises matches a record that is relevant to that site, and only after a trained analyst has reviewed the match.

What happens to everything else

When an image captured at a facility does not match a relevant record, it is deleted immediately. No biometric template is stored. Nobody builds a history of who walked through the door.

Why this matters

Identity technology is only as trustworthy as its source data. A larger database built from anything that can be found online is not a better database. It is a less accountable one. We would rather be able to answer, for every single record, where it came from.

Questions about how the database handles personal data can go to our privacy team through the privacy page.

Featured photo by MIKE STOLL on Unsplash.

What residents are rejecting when a city cancels its plate readers

Posted on October 12, 2026October 12, 2026 by Safience

In the space of three days this month, two local governments walked away from the same kind of system.

On 6 October, Henrico County, Virginia, ended its automated license plate reader contract early. The county had installed more than 120 of the cameras since November 2022 and spent about $1 million on them. County Manager John Vithoulkas put the problem plainly: “it seems like every day, there’s another issue with another locality and how Flock cameras are used.” Two days later, Reno said it would not renew its agreement with Flock Safety, after residents argued that cameras logging every passing vehicle into a searchable database violated their privacy and constitutional rights.

Neither was first. Reporting in January counted at least six jurisdictions, including Flagstaff, Arizona, Cambridge, Massachusetts and Evanston, Illinois, that had cancelled or terminated contracts. Some cited residents’ privacy concerns. Cambridge and Evanston cited cameras installed or reinstalled without the city’s knowledge.

What the objection actually is

Look at the reasons given in Reno, Henrico and the cities before them and a pattern shows up. The complaint is not that police find stolen cars or wanted people. The complaint is the method: record everyone who passes, keep it, and search it later.

Henrico’s system kept images for 21 days. Every driver who passed a camera in that window, suspected of nothing, sat in the searchable set. That is the design choice that keeps losing votes. Not the goal. The collection.

Start from the other end

There is another way to build identity technology for public safety, and it begins at the opposite end. Instead of collecting everything and searching it later, you start from a short list of records a court or agency has already created, and you ask a narrow question about a single moment: does this person match one of them?

That is the model Safience is built on.

Records first. Every comparison runs against UMbRA, the law-enforcement-sourced identity database, which holds 58.5M+ records and draws on nothing else. No social media, no news photos, no commercial data.

Nothing kept on anyone else. A facility captures a single still image. If it does not match a relevant record, it is deleted at once and no biometric template is stored. There is no history of who walked past.

No video, no plates. Safience never receives, records or stores video. It does not read license plates or follow vehicles.

A person before the alert. A trained analyst reviews every potential match before anyone is told. A resemblance is not treated as an identity.

Five questions for the next council vote

Reno staff plan to bring a contract with a different vendor to the council on 21 October. Whatever that council decides, and whatever any other council decides, the questions that tend to settle public comment are the same.

Who is in the searchable set: everyone who passes, or only people with an existing record?
How long is data about people who are not suspects kept, and who can search it in that time?
Can the vendor add cameras, sharing partners or features without a public vote?
Who reviews a result before an officer acts on it?
Will the vendor publish its use policy in plain language?

A vendor that answers the first two with “everyone” and “weeks” is asking a council to defend mass collection at the microphone. Recent votes show how that tends to end.

The short version

Public safety tools are losing votes because they collect too much, not because residents are against public safety. A system that starts from a verified record, keeps nothing on anyone else and puts a trained person between the match and the action gives a council something it can stand behind.

For how a single record-bound match works in practice, see Identity intelligence starts with a record, not a face. For how biometric rules differ by state, see our state privacy policy pages. Agencies and councils with questions can reach us through contact.

Sources

VPM News, “Henrico cancels Flock Safety contract early over ‘privacy concerns’,” 6 Oct 2026. https://www.vpm.org/news/2026-10-06/henrico-police-cancel-flock-safety-alpr-vithoulkas-cooper-newby/
KOLO 8, “City of Reno will not renew its contract with Flock Safety over privacy concerns,” 9 Oct 2026. https://www.kolotv.com/2026/10/10/city-reno-will-not-renew-its-contract-with-flock-safety-over-privacy-concerns/
Straight Arrow News, “‘Democracy in action’: Cities react to privacy concerns by canceling Flock surveillance contracts,” 8 Jan 2026. https://san.com/cc/democracy-in-action-cities-react-to-privacy-concerns-by-canceling-flock-surveillance-contracts/

Featured photo by Michael D Beckwith on Unsplash.

A match is only as good as the record behind it

Posted on September 25, 2026 by kmurali@biometrica.com

A stop or an arrest that starts from an identity match fails in one of two places. The comparison can be wrong. Or the record that was compared was never a verified record of that person. The second failure is a database failure. It is not fixed by a better algorithm.

Two cases from this month show the second failure. Neither one is an argument about a vendor’s finances.

Plymouth: the plate in the database was not the plate on the car

On 22 September 2026 the Plymouth, Minnesota city council voted 6 to 1 to end its contract for automated license plate readers and to have the cameras removed. The city has 16 of them. The vote was reported the next day by MPR News and by the Sun Sailor.

The incident the council had in front of it was from late June. Joel Feder was stopped in a Kohl’s parking lot by Plymouth officers after the readers alerted on his plate. His New Jersey manufacturer plate read “34 10 DTM”. The alert matched a shorter plate, “34 DTM”. Plymouth police said the stolen-plate entry in the National Crime Information Center had been made in California on 24 June 2026 with incomplete numbers. Officers got alerts on 26 June and 28 June. The 28 June alert is the day of the stop.

The reader and the database did not agree with the plate on the car. Officers still had a car full of police in a parking lot because a stored string said the plate was stolen. Flock’s own statement, given to FOX 9 and to WCCO, was that an alert is a lead and that officers should verify the plate before they act. The council voted to take the cameras out anyway.

Sources:

Fargo: the photo that was searched was on a fake ID

On 17 September 2026 Biometric Update reported a federal complaint by Angela Lipps of Elizabethton, Tennessee, against the City of Fargo and Detective Lucas Heck. The complaint seeks $10 million. The Guardian reported the suit the next day.

The complaint says Lipps had never been to North Dakota, did not look like the person on the bank video, and was not identified by any bank witness. It says, on information and belief, that the facial-recognition search was run on the photograph printed on a fraudulent identification card the suspect had used, not on a still from the surveillance video of the person who was in the bank. ABC News reported that Fargo’s police chief later said detectives had wrongly assumed the surveillance photos were part of that search, and that they were not.

That is a source-data failure. A match against the picture on a fake document identifies the document. It does not identify a person who was booked, printed, and charged. Treating that match as probable cause for an arrest warrant is the step the complaint challenges. The suit is a set of allegations. It is not a judgment.

Lipps was arrested in Tennessee in July 2025 and held for about six months before the charges were dismissed, according to the Guardian’s account of the filing.

Sources:

What changes if the record has to come from a booking

UMbRA is the law-enforcement-sourced identity database behind Safience. A record in it is there because an agency booked, convicted, registered, or listed the person, not because a camera misread a plate and not because a picture was taken from a document the suspect printed. The current size of that file is on the UMbRA page and is updated by the site. This story does not state a number. https://safience.io/umbra/

A match against that file is still a lead. A person checks it before an alert goes to a customer. The Plymouth stop and the Fargo arrest both skipped that kind of check: the stored string, or the stored photo, was treated as the person.

The councils and the courts are not arguing about model accuracy in these two cases. They are arguing about whether anyone can show where the matched record came from, and whether a person looked at it before someone was stopped or jailed.

Drug Offenses Made Up Nearly One-Third Of All Cases In FY 2022: USSC Report

Posted on March 24, 2023August 23, 2026 by kmurali@biometrica.com

By a Biometrica staffer

Drug related offenses accounted for almost one-third of all cases reported in fiscal year 2022, the United States Sentencing Commission (called “the Commission” hereon) said in its annual report. That makes drug offenses the single largest category of offenses reported. Only two years ago, in comparison, immigration related offenses made up the single largest group (in FY 2020).

The courts also reported 64,142 felony and Class A misdemeanor cases to the Commission in FY 2022, it added in the report. That represents an increase of 6,855 cases from FY 2021.

In FY 2022, 47.4% of all offenders were Hispanic, 25.2% were Black, 23% were White, and 4.4% were of another race. This is largely unchanged from previous years. Non-U.S. citizens accounted for 31.2% of all offenders, a decrease of 2.4 percentage
points from the prior year, the report adds.

When it comes to the sentences, 67.8% of all offenders received sentences under the Guidelines Manual, “in that the sentence was within the applicable guideline range or was outside the applicable guideline range and the court cited a departure reason from the Guidelines Manual,” the report said. About 41.9% of all sentences were within the guidance range, compared with 42.8% in FY 2021.

Of the total cases reported to the Commission in FY 2022, 89% of them received a prison only sentence, 3.1% were given prison and alternatives, 1.6% were given probation and alternatives, 5.8% were given probation only, and 0.5% were given a fine only.

Fentanyl Cases On The Rise

Within drug related offenses, drug trafficking made up for a majority of the cases reported at 19,938. The number of drug trafficking cases reported to the Commission increased by 2,330 in FY 2022. In contrast, the number of drug possession related cases were marginally lower at 296 in FY 2022 versus 309 in the previous year.

What is worrisome, though, is that the number of cases involving fentanyl “increased markedly” over the last year. Fentanyl cases were the third most common among all drug offenses reported to the Commission. Authorities have, in the recent past, termed fentanyl the “deadliest drug threat” the country has ever faced.

Just this Tuesday, March 21, the U.S. Drug Enforcement Administration (DEA) warned the American public of a sharp increase in the trafficking of fentanyl mixed with xylazine. Xylazine and fentanyl drug mixtures place users at a higher risk of suffering a fatal drug poisoning.

Around 66% of drug poisoning deaths between August 2021 and August 2022 involved synthetic opioids like fentanyl, the DEA said in its public safety alert citing data from the Centers for Disease Control and Prevention (CDC).

Among drug offenses, those involving methamphetamine were most common and made up for 48.5% of all drug cases reported to the Commission in FY 2022.

In FY 2022, 64.7% of drug offenders were convicted of an offense carrying a mandatory minimum penalty, compared to 67.7% of drug offenders in FY 2021, the report says.

The average length of imprisonment in methamphetamine cases was 94 months, an increase of four months from FY 2021, the Commission added. However, the average sentence varied across the other major drug types. It was:

70 months in crack cocaine cases
68 months in powder cocaine cases
65 months in fentanyl cases
66 months in heroin cases
33 months in marijuana cases

For more information and to access the full annual report from the United States Sentencing Commission, click here.

Early Gangs Of Britain and America: The ‘Mohocks,’ And The Forty Elephants

Posted on March 2, 2023August 19, 2026 by kmurali@biometrica.com

By a Biometrica staffer

London in the late 17th and 18th centuries was a rather challenging place to live in, going by one specific measure: the presence of gangs. Certain parts of the city had gained such notoriety as hotbeds of crime that people were vary of venturing into those areas. The street gangs that roamed London back then were structured like modern-day gangs. In other words, they could be considered early examples of what is known today as ‘organized crime.’

This is the first in a series of pieces Biometrica plans to do on some notorious early gangs of Britain and America. Given the movement of people between the two, there are shared histories and stories of gangs that caused a stir on both sides of the Atlantic, like Alice and her all-women band of thieves.

In the rest of this piece, we take you back in time to London of the 18-20th centuries. These predecessors of organized crime gangs and syndicates were many and varied, and women were as much a part of this planned violence as men. We examine two infamous early examples from Britain in the following sections of the piece.

The ‘Mohocks’

A chilling rumor began to do the rounds in the year 1712 in London. Tales were told about a group of men who met at “coffee houses and taverns in the night, drank copiously,” then ventured out onto the streets assaulting and beating innocent passers-by, destroying property, and frightening the public. These men reportedly belonged to the social elite, according to a journal article, titled The Case Of The Mohocks: Rake Violence In Augustan London.

This gang’s forte was committing sensational crimes in the heart of the city, building on the fears of the sort of street violence that was considered endemic in early modern London. They had assigned themselves the name ‘Mohocks,’ misappropriated after tribes in what was then British North America, whom the gang considered “savages,” per the journal article.

Their alleged exploits were catalogued in such vivid detail across newspapers, periodicals, and the like, that it resulted in general panic in London. People were afraid to venture outdoors after dark, and the crown even issued a proclamation offering a reward for the capture of any member of the Mohocks.

The interesting part of the whole Mochocks episode is that nobody knows how much of it was real, and how much was an illusion created by an overactive public imagination, fueled by London’s endemic street violence, “sensational reports” of the gang’s alleged exploits, and “political opportunism,” the journal report adds.

It is generally agreed that there were gangs of men roaming about London and wreaking havoc, like the Mohocks allegedly did. And there was good reason for the public to panic, or to assume the worst about the Mohocks.

In the early 1600s, there were quite a few infamous gangs running amok in London, including the Mims, Hectors, Bugles, and Dead Boys. These gangs “found amusement in breaking windows, [and] demolishing taverns, [and they] also fought pitched battles among themselves dressed with colored ribbons to distinguish the different factions (Pearson, 1983, p. 188),” according to a Bureau of Justice Assistance National Gang Center Bulletin report titled History Of Street Gangs In The United States.

The very first reports of the Mohocks appeared in February of 1712. By summer of the same year, the episode and the panic surrounding the gang had faded into nothing but a “potent memory,” the journal report says.

Alice And The Elephants

If you thought the cold professionalism with which gangs appear to operate was the forte of only men in the past, you’d be surprised to learn about Alice Diamond and her mob of organized thieves. In the first half of the 20th century, this gang gained infamy by pilfering expensive luxury fashion goods. But, do not mistake them for petty shoplifters.

The Forty Elephants, as the gang was known (sometimes referred to as The Forty Thieves), allegedly operated almost like a modern corporation. They even had their own code of conduct called the ‘Hoister’s Code,’ according to a local media report based on a book by Brian McDonald. No drinking the night before a job, not wearing stolen outfits (on a job, presumably), and never helping the police were all part of the Hoister’s Code, per the media report.

Loyalty was considered really important as gang members were frequently arrested. Fictional alibis were crafted and supplied by fellow gang members whenever one of them was arrested, and they even set aside money to look after families of the arrested member.

Hoisting was the preferred modus operandi of this gang and the West End of London was their favorite hunting grounds. West End hosts many of the city’s stores, businesses, and other tourist and entertainment attractions.

The gang would steal from stores and shove the stolen goods, mostly luxurious outfits made of fur or other expensive fabric, down their specially crafted voluminous underwear with elastic at the knees to hold the loot. They were otherwise dressed for the part, too, in immaculate outfits and “beautifully coiffed hair,” writes journalist and author Beezy Marsh.

The gang was also structured in such a way that they operated in smaller groups of four or five, per the media report on McDonald’s book Alice Diamond and The Forty Elephants. These smaller groups were assigned a particular area to operate in for a period. They would identify and observe their targets before carrying out a job.

While they were carrying out the job, a few of the ‘hoisters’ would act as decoys to distract store assistants while their accomplices could do the actual ‘hoisting’ of jewels and expensive clothes. Their strategy involved using the recognizable members of the gang as decoys. These decoys would distract store employees by feigning a pilfer at one end, while their accomplice did the actual stealing in another part of the store.

The gang also developed a violent reputation somewhere along the line. Anyone who crossed them — whether law enforcement or a member of a rival gang — would find themselves at the receiving end of a sharp hatpin, which they allegedly also used to blind their victims, or sliced by a razor that was carefully concealed in a lace handkerchief.

And at the helm of this highly organized, all-female gang was their Queen, Alice Diamond. She was allegedly nearly six feet tall (at a time when many men weren’t), was beautiful, had a cool demeanor, and could throw a punch as strong as any man.

Her numerous bejeweled rings that doubled up as “knuckle-dusters” probably added to the weight of those punches. She took over control of the gang when she was allegedly in her twenties.

Tales of the gang’s exploits were well known across the Atlantic, and elsewhere around the world. Although members of the gang were arrested often, their well defined structure, oddly strong work ethic, their intelligence, and their ‘Queen’s’ prowess as a leader presumably helped them maintain their hold over London for over two decades.

Watch out for more from Biometrica on early gangs of Britain and America.

How You Can Help In The Fight Against Human Trafficking

Posted on January 27, 2023March 15, 2026 by kmurali@biometrica.com

By a Biometrica staffer

Anyone can, potentially, help in the battle against human trafficking. How? One possible place to start is by learning and researching on spotting some typical signs and indicators of this tragic crime. So, if you happen to come across someone you think may be a victim of trafficking, you can alert the authorities.

That said, at the very outset, it’s important for us to address a few key aspects. One, while learning the signs is definitely a good place to begin, in order to be better equipped to make an informed, unbiased decision to report a potential trafficking situation, we would urge you to learn how trafficking really happens on the ground, by reading and listening to victims and survivors through organizations like Polaris.

Another crucial aspect to consider is that not all human trafficking situations may have visible signs or indicators. So, in some cases, it may be near-impossible for someone who doesn’t know the victim well to spot the signs by just happening to pass by, for instance.

The third crucial point to remember is: Once you have learnt about the typical indicators and the reality of human trafficking cases, and perhaps come across a potential situation, the best course of action is to alert law enforcement and not to try and rescue the victim on your own, or involve yourself on the ground in any other manner.

As we come to a close of this year’s Human Trafficking Awareness Month, we take you through the various signs that experts have listed as possible red flags of trafficking, so you can begin to equip yourself to do your bit in the battle against it.

Note: If you are a human trafficking victim or if you have information about a potential trafficking situation, call the National Human Trafficking Resource Center Hotline at 1-888-373-7888 or text 233733. This national, toll-free hotline has specialists available to answer calls from anywhere in the country, 24 hours a day, seven days a week. You can also submit a tip at humantraffickinghotline.org.
For urgent situations, notify local law enforcement immediately by calling 911, and also alert the National Human Trafficking Hotline.

Human Trafficking In The U.S.

Each year, several children and adults are trafficked worldwide. There were over 1,675 pending FBI cases as of this month, the Federal Bureau of Investigation’s (FBI) Springfield division said in a statement. In fiscal year 2022, the FBI initiated 668 human trafficking investigations.

It’s also important to note that these cases were not restricted to specific geographies within the United States. All 56 FBI field offices have reported incidents, the FBI Springfield statement adds.

The largest percentage and greatest number of sex trafficking victims recovered in the United States are U.S. citizens, the statement continues. Conversely, the largest percentage of labor trafficking victims recovered in the U.S. are non-U.S. citizens.

About 90% of the FBI’s human trafficking cases involve sex trafficking, while the remainder involves labor trafficking. However, the FBI cautions that there may be a greater number of victims of labor trafficking.

“Human trafficking isn’t always a violent crime—but it is always a devastating crime that is happening with shocking frequency right here in the United States,” FBI Springfield Field Office Special Agent in Charge David Nanz said in the statement.

Source: Iowa Secretary of State Paul Pate’s YouTube channel. Video in partnership with Chains Interrupted, an organization involved in fighting against human trafficking.

Human Trafficking Red Flags

It’s not possible to create an exhaustive list of the signs, indicators, or describe the realities of human trafficking cases. However, we’ve combed through various sources — including the U.S. Department of State, FBI, Department of Homeland Security, the National Human Trafficking Hotline, Polaris, and Chains Interrupted — to try and give you as detailed a perspective as we can.

Before we get into the typical indicators to look out for, it’s important, again, to stress that learning to recognize these signs is only an introduction to how human trafficking takes place. And, if you do spot any one of these signs, it may not necessarily mean you’ve stumbled upon someone being trafficked.

For example, the fact that a person is living with their employer need not necessarily be a sign of labor trafficking. However, if someone is living with their employer in what appears to be an unsuitable condition, appears to have no personal possessions, appears to be kept isolated, isn’t allowed to interact with anyone without ‘supervision,’ and doesn’t have their own identification and travel documents, there’s a high possibility that they are being trafficked.

It’s also worthy to note that not all human trafficking involves physical abuse, or signs of it, or sexual abuse. We also have to pause to say that while human trafficking can, indeed, happen to anyone, anywhere, there are certain people that are definitely more vulnerable to it than others. We’ll address that and discuss types of trafficking in a separate piece.

For now, here’s a list of indicators compiled from across the sources we mentioned above (listed in question form).

Labor Trafficking Indicators

Living and working conditions:
Is the person living with their employer?
Do their living conditions seem poor or inadequate?
Are there multiple people living in a cramped space?
Are there locks on the outside, rather than the inside, of where they are living?
Are they cut off from interacting with others and kept isolated?
Are they allowed to, and/or given, access to food, water, medical care, and other life necessities?
Does it appear like they have, or are allowed to have, any personal possessions?
Do they show signs of having been denied food, water, sleep, or medical care?
Are they being pressured to work in dangerous conditions without proper safety gear, other protection, training, adequate breaks, etc?
Monitored and controlled:
Are they constantly watched, or being guarded, by someone?
Are they often (or always) seen only in the company of someone to whom they defer, or to someone who seems to be in control of the situation?
Does it seem like they’ve been coached on what to say?
Is the person fearful, timid, or submissive?
Are they allowed to move freely? Can they freely leave where they live?
Are they allowed to speak with family members, friends, or be in contact with other members of their community?
Was the victim recruited for a particular purpose but is now being forced to do something else instead?
Do they appear to have unreasonable duties/expectations?
Do they work excessively, and unreasonably, long hours, and particularly so after dark?
Wages and documents:
Are they in possession of their own travel papers and other documents?
Are their wages being used to “pay off a debt or a fee?”
Are they allowed to access their own bank accounts, and allowed to be in control of their money?
Have they been threatened with deportation or criminal charges by their employer?

Sex Trafficking Indicators

Behavior change:
Has a person, adult or child, had a sudden and, perhaps, dramatic change in behavior?
If it’s a child, has the child stopped attending school?
Similarly, if it’s an adult who had a job, have they suddenly stopped going to work?
Are they disoriented or confused, or showing signs of mental or physical abuse?
As with cases of labor trafficking, do they appear fearful, timid, or submissive?
Are they transported under supervision or with guards between where they live and their workplace?
Does it appear that they have someone controlling or monitoring them constantly?
If they appear to be controlled, are they kept isolated and not allowed to interact with others?
The more obvious signs:
Does the child or adult appear to have bruises, in various stages of healing?
Is the person, adult or child, being forced to perform sexual acts?
Do they want to stop participating in commercial sex activities, but feel scared or are unable to get out of the situation?
Have they disclosed to you, or to someone else, that they were pressured into engaging in commercial sex acts?
Do they (especially child victims) seem to have a pimp or a manager in the commercial sex industry?
Do they work in industries where it may be more common to be pressured into performing sex acts for money, like strip clubs, illicit cantinas, illicit massage parlors etc?
Important note: If the victim is a child under the age of 18, and involved in commercial sex, they are legally considered a victim of trafficking. While for any other case of trafficking, force, fraud or coercion must be present, child victims involved in commercial sex are the exception to the rule. Under federal law, there’s no such thing as child prostitute.

Some labor trafficking indicators may also apply to instances of sex trafficking, and vice versa. Each case is unique.

Where To Get Help

The State Government website says: “If you believe you have identified someone still in the trafficking situation, alert law enforcement immediately. It may be unsafe to attempt to rescue a trafficking victim. You have no way of knowing how the trafficker may react and retaliate against the victim and you.”

“If, however, you identify a victim who has escaped the trafficking situation, there are a number of organizations to whom the victim could be referred for help with shelter, medical care, legal assistance, and other critical services. In this case, call the National Human Trafficking Hotline described below.”

To reiterate: If you are a human trafficking victim or if you have information about a potential trafficking situation, call the National Human Trafficking Resource Center Hotline at 1-888-373-7888 or text 233733. This national, toll-free hotline has specialists available to answer calls from anywhere in the country, 24 hours a day, seven days a week. You can also submit a tip at humantraffickinghotline.org.
For urgent situations, notify local law enforcement immediately by calling 911, and also alert the National Human Trafficking Hotline.